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Pura, Megantara
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Public Health Social Sciences

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Automatic Mass Waste Sorting System Using Inductive Proximity Sensor, Water Level Sensor and Image Processing using MobileNet Algorithm Pura, Megantara; Langko, Charles Hardi; Kho, Jason
Ultima Computing : Jurnal Sistem Komputer Vol 15 No 2 (2023): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v15i2.3421

Abstract

The global municipal solid waste is predicted to increase by threefold in 2050. Indonesia’s most wastes are unsorted and only end up in landfill and the waste management is less than ideal. An automatic mass waste sorting system is proposed to answer such problems. The automatic mass waste sorting system is designed to be able to identify and separate metal, plastic and organic waste using electrical sensors and image processing. The electrical sensors was able to identify waste types with 65% accuracy and the image processing system was able to identify waste types with 86.67% accuracy. The result doesn’t offer much advantage compared to other research on waste management system, however it is hoped that this research may inspire other researches on mass waste sorting systems.
ALAT PENGUKUR KESEHATAN UNTUK DETEKSI AWAL GEJALA COVID-19 DI PUSKESMAS KELAPA DUA Pura, Megantara; Muharrom, Ahmad Syahril; Nugraha, M.B; Winantyo, Rangga; Tampubolon, Marojahan; Tanex, Kevin Nicholas; Kristi, David
Jurnal Sinergitas PKM & CSR Vol. 6 No. 2 (2022): OCTOBER
Publisher : Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/jspc.v6i2.6151

Abstract

Sebagai bentuk kepedulian terhadap pencegahan penyebaran virus COVID-19, dibuat alat pengukur kesehatan yang akan diaplikasikan di puskesmas. Alat yang dibuat dapat mengukur temperatur tubuh, detak jantung, dan kadar oksigen dalam darah menggunakan teknik photoplethysmography. Alat ini juga berfungsi untuk menghubungi petugas puskesmas bila kondisi kesehatan pasien menurun menggunakan sistem short messaging services (SMS). Mikrokontroller Arduino Mega 2560 digunakan sebagai penerima data dan kendali sistem. Sensor yang digunakan adalah sensor temperatur MLX90614 dan sensor kadar oksigen MAX30102. Sistem pengiriman SMS menggunakan board SIM808. Alat ini beroperasi menggunakan sumber listrik AC, dengan baterai Li-ion sebagai cadangan catu daya. Pengujian alat dilakukan di pintu masuk Laboratorium Teknik Elektro Universitas Multimedia Nusantara. Setiap mahasiswa yang datang ke laboratorium tersebut wajib melakukan cek kesehatan menggunakan alat tersebut. Selama masa pengujian, alat dapat mendeteksi temperatur dan kadar oksigen mahasiswa dengan tepat, serta alat mampu bertahan selama satu hari penuh hanya dengan menggunakan baterai. Alat ini akan diletakkan dan diaplikasikan di Puskesmas Kelapa Dua Tangerang.
Automatic Mass Waste Sorting System Using Inductive Proximity Sensor, Water Level Sensor and Image Processing using MobileNet Algorithm Pura, Megantara; Langko, Charles Hardi; Kho, Jason
ULTIMA Computing Vol 15 No 2 (2023): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v15i2.3421

Abstract

The global municipal solid waste is predicted to increase by threefold in 2050. Indonesia's most wastes are unsorted and only end up in landfill and the waste management is less than ideal. An automatic mass waste sorting system is proposed to answer such problems. The automatic mass waste sorting system is designed to be able to identify and separate metal, plastic and organic waste using electrical sensors and image processing. The electrical sensors was able to identify waste types with 65% accuracy and the image processing system was able to identify waste types with 86.67% accuracy. The result doesn't offer much advantage compared to other research on waste management system, however it is hoped that this research may inspire other researches on mass waste sorting systems.
Co-Authors Kho, Jason Kristi, David Langko, Charles Hardi Marojahan Tampubolon Muharrom, Ahmad Syahril Nugraha, M.B Rangga Winantyo, Rangga Tanex, Kevin Nicholas